BloomBench - Arabic - Understand: leaderboard

BloomBench (Almieyar-Oryx series, QCRI, 2026) is a bilingual English and Arabic multiple-choice benchmark for vision-language models organized by the six levels of the revised Bloom taxonomy, scored as zero-shot accuracy in percent from the answer letter parsed from generated text (chance 25). This board is accuracy on the 1,592 Modern Standard Arabic items of the Understand level (compositional scene understanding, emotions and semantic knowledge); higher is better.

Metric: Accuracy (%) on the 1592 Arabic BloomBench items at the Bloom level Understand (compositional and cognitive understanding: relations, emotions, semantics), four-option image-question multiple choice, zero-shot, temperature 0, the chosen letter parsed from the generated answer (Regex-based Answer Extraction; unparseable answers count as wrong); chance 25; higher is better. Source: arxiv.org. Saturation forecast: Estimated already saturated. 8 models tracked.

Top models

#ModelScoreOverall rank
1Gemma 3 27B93#1631
2Gemma 3 12B92#2000
3Gemma 4 31B91#394
4Gemma 4 26B A4B89#615
5Qwen 2.5 VL 7B87#1787
6GPT-4o Mini86#1623
7Qwen 2 VL 7B86#2261
8Gemma 3 4B84#5064

No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.

Interactive version: theaggregate.ai/benchmark?slug=bloombench-arabic-understand · How It Works · Data refreshed daily, snapshot 2026-11-13.